identification and genome-wide prediction of dna binding

Identification and Genome-Wide Prediction of DNABinding Specificities for the ApiAP2 Family of Regulatorsfrom the Malaria ParasiteTracey L. Campbell1, Erandi K. De Silva1, Kellen L. Olszewski1, Olivier Elemento2, Manuel Llinas1*

1 Department of Molecular Biology & Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America, 2 Institute for

Computational Medicine, Weill Cornell Medical College, New York, New York, United States of America

Abstract

The molecular mechanisms underlying transcriptional regulation in apicomplexan parasites remain poorly understood.Recently, the Apicomplexan AP2 (ApiAP2) family of DNA binding proteins was identified as a major class of transcriptionalregulators that are found across all Apicomplexa. To gain insight into the regulatory role of these proteins in the malariaparasite, we have comprehensively surveyed the DNA-binding specificities of all 27 members of the ApiAP2 protein familyfrom Plasmodium falciparum revealing unique binding preferences for the majority of these DNA binding proteins. Inaddition to high affinity primary motif interactions, we also observe interactions with secondary motifs. The ability of anumber of ApiAP2 proteins to bind multiple, distinct motifs significantly increases the potential complexity of thetranscriptional regulatory networks governed by the ApiAP2 family. Using these newly identified sequence motifs, we inferthe trans-factors associated with previously reported plasmodial cis-elements and provide evidence that ApiAP2 proteinsmodulate key regulatory decisions at all stages of parasite development. Our results offer a detailed view of ApiAP2 DNAbinding specificity and take the first step toward inferring comprehensive gene regulatory networks for P. falciparum.

Citation: Campbell TL, De Silva EK, Olszewski KL, Elemento O, Llinas M (2010) Identification and Genome-Wide Prediction of DNA Binding Specificities for theApiAP2 Family of Regulators from the Malaria Parasite. PLoS Pathog 6(10): e1001165. doi:10.1371/journal.ppat.1001165

Editor: Joe D. Smith, Seattle Biomedical Research Institute, United States of America

Received May 5, 2010; Accepted September 27, 2010; Published October 28, 2010

Copyright: � 2010 Campbell et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was funded by the NIH (R01 AI076276; http://grants.nih.gov/grants/oer.htm) and the Arnold and Mabel Beckman Foundation (http://www.beckman-foundation.com/index.html) with support from the Center for Quantitative Biology (P50 GM071508; http://quantbio.princeton.edu/) (ML). TLC wasfunded by an NSERC Postdoctoral Fellowship (http://www.nserc-crsng.gc.ca/) and KLO is supported by an NSF Graduate Research Fellowship (http://www.nsfgrfp.org/). OE is supported by start-up funds from the HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine (http://icb.med.cornell.edu/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

Introduction

Plasmodium falciparum is responsible for the majority of human

malaria cases and causes approximately 1 million deaths every

year [1]. The complete lifecycle of P. falciparum includes three

developmental stages, which occur in its mosquito vector, the

human liver, and human blood. Within each developmental stage

the parasite undergoes major morphological changes that are

accompanied by precisely timed transcription of genes that are

necessary for parasite growth, differentiation, and replication.

Detailed transcriptome and proteome studies have been conduct-

ed across the different stages of the life cycle [2–12]. Despite these

advances in our understanding of messenger RNA transcript

dynamics in P. falciparum, very little is known regarding the

mechanism of transcriptional regulation, including transcription

factor binding and sequence specificity.

Basic transcriptional control in P. falciparum appears to resemble

that of other eukaryotic organisms, with general transcription

factors coordinating the recruitment of RNA polymerase II to core

promoter elements [13–15]. Experiments aimed at identifying cis-

acting sequences required for gene expression have successfully

identified specific enhancer and repressor sequences upstream of

the core promoter elements [16–26]. In the asexual blood stage,

regulatory sequence elements have been identified for the gene

encoding the knob-associated histidine-rich protein (kahrp) [16],

glycophorin binding protein 130 (gbp130) [18], cytidine diphos-

phate-diacylglycerol synthase (pfcds) [19], the DNA polymerase

delta gene [20], a subset of the heat shock protein (hsp) family [22],

the rif genes [23] and the falcipains [24]. Additionally, three

sequence motifs have been identified upstream of the var genes: the

SPE1, CPE, and SPE2 motifs, of which the SPE2 motif has been

hypothesized to be involved in silencing of var gene expression

[25,26]. In sexual blood stage parasites three distinct short

sequence elements have been found to regulate expression of the

gametocyte genes pfs16, pfs25 [17], and pgs28 [21]. In addition to

these experimentally derived motifs, bioinformatic analyses of the

P. falciparum genome have identified a number of potential cis-

elements that may play a role in gene regulation [27–36].

However, attempts to identify trans-factors have been largely

unsuccessful [13,15,37,38], with the exceptions of Myb1 [39,40]

and the high mobility group box (HMGB) proteins [41,42].

Recently, a large protein family was identified in P. falciparum,

containing Apetala2 (AP2) domains [43]. AP2 domains were

originally described in plants as DNA binding domains approx-

imately 60 amino acids in length [44]. In plants, the AP2 family of

transcription factors is one of the largest, playing key roles in

developmental regulation [44] and stress responses [45]. The

Apicomplexan AP2 (ApiAP2) proteins represent a lineage-specific

PLoS Pathogens | www.plospathogens.org 1 October 2010 | Volume 6 | Issue 10 | e1001165

expansion, and are highly conserved across all Plasmodium spp. and

in other Apicomplexans including Theileria, Cryptosporidium [43] and

Toxoplasma [46]. P. falciparum was initially predicted to contain 26

ApiAP2 factors, each containing one to three AP2 domains [43],

while in Toxoplasma the family is expanded to over 50 ApiAP2

proteins [46]. We have noted a 27th highly conserved ApiAP2

protein (PF13_0267), which agrees with recent Pfam predictions

for this protein [47]. Although other DNA binding proteins have

been reported in the literature, ApiAP2 proteins represent the

largest family of transcriptional regulators identified in P.

falciparum, where they are expressed throughout the entire

developmental lifecycle [43].

Previously, we established that two ApiAP2 proteins,

PF14_0633 and PFF0200c, bind DNA with high sequence

selectivity [48]. Subsequent work demonstrated that the P. berghei

orthologue of PF14_0633 (PBANKA_132980) is essential for the

formation of sporozoites [49], and specifically regulates sporozoite

target genes by binding to the same GCATGCA motif that we

identified [48]. More recently, PFF0200c was shown to function as

a DNA tethering protein involved in heterochromatin formation

and integrity [50] via binding to the previously identified SPE2

motif [25]. Importantly, PFF0200c does not appear to act as a

transcriptional regulator in the blood stage. A third study

identified a P. berghei protein, AP2-O [PBANKA_090590

(PF11_0442)], as an activator of genes required for invasion of

the mosquito midgut during the mosquito stage of the life cycle

[51]. Together, these studies highlight the importance of the

ApiAP2 DNA binding proteins in modulating stage-specific gene

regulation and chromatin integrity. Despite these recent advances,

the regulatory function of the majority of ApiAP2 proteins remains

unknown. The DNA sequences recognized by the members of this

protein family are largely uncharacterized, and the target genes

that these ApiAP2 factors bind are undefined.

Here we biochemically and computationally characterize the

global DNA binding specificities for the entire ApiAP2 protein

family from P. falciparum. Our results reveal a complex array of

DNA sequence elements, with the majority of proteins binding to

unique sequences. We demonstrate several cases where multiple

AP2 domains within the same ApiAP2 protein are capable of

binding distinct DNA sequences. The identification of these

unique sequence motifs sheds light on the molecular mechanisms

of transcriptional regulation by assigning correlations between

putative cis-acting sequences in Plasmodium and the trans-factors

that will bind at those sequences genome-wide. Our data reveal

the likely identity of trans-acting ApiAP2 factors that specifically

bind to previously described cis-motifs, illuminating some of

the previously unknown effectors of plasmodial gene expres-

sion. For the many new motifs we identified, we predict putative

targets for each of the ApiAP2 proteins. This work represents

the first comprehensive analysis of the ApiAP2 DNA bind-

ing proteins in P. falciparum and provides a crucial missing link

toward understanding their role in the regulation of parasite

development.

Results

P. falciparum ApiAP2 Domains Bind Diverse SequenceElements

The 27 plasmodial ApiAP2 proteins vary drastically in size

(Figure S1), however, the predicted 60 amino acid AP2 domains,

are well-defined and highly conserved. To determine the DNA

binding specificity for the P. falciparum AP2 domains, we used

protein binding microarrays (PBMs), which enable simultaneous

screening of all possible DNA sequences up to ten nucleotides in

length without sequence bias [52,53]. Seminal studies from the

Bulyk lab have used PBMs to comprehensively characterize

individual transcription factors from a diverse array of organisms

including yeast, worm, mouse and human [52–54]; and we have

previously demonstrated its utility for Apicomplexan AP2 DNA

binding proteins [48].

We created 50 constructs for PBM screening (Supplemental

Text S1, Figure S2), including individual domains, full length

proteins, and tandem domain arrangements (two AP2 domains

separated by a short conserved linker sequence of 12 to 79 amino

acids; designated DLD). Our analysis by PBM of these P. falciparum

AP2 domains revealed motifs for 20 out of the 27 ApiAP2 proteins

(Figure 1), including a motif for the recently identified ApiAP2

protein, PF13_0267, helping to confirm the new annotation for

this protein. Results from at least two PBM experiments for each

AP2 domain were used to generate position weight matrices

(PWMs), which represent the DNA binding affinity for a given

domain (Dataset S1, Figure 1). Replicate experiments had

excellent correlation coefficients illustrating the robustness of the

PBM methodology (see Supplemental Text S1). Enrichment scores

(E-scores) were assigned for each 8-mer (allowing up to two gaps)

[53], with a significance cut-off of 0.45 (E-scores range from -0.5 to

+0.5) for specific 8-mers enriched above background. The E-score

is a rank-based, nonparametric score that is robust to differences in

protein concentration and reflects the relative preference for each

8-mer [55]. In total we identified sequence motifs for 24 AP2

domains found in a variety of protein architectures (Figure 1).

While Figure 1 illustrates which motifs are linked to the blood

stage of Plasmodium development, several motifs are also associated

with ApiAP2 proteins during non-blood stages as well (see

Supplemental Text S1). It is noteworthy that different AP2

domains from the same ApiAP2 protein bind distinct DNA

sequence elements. However, we do find several motifs that are

recognized by multiple ApiAP2 factors (see Supplemental Text S1

and Table S1). This complexity may allow for multifaceted

transcriptional regulation using a smaller number of individual

factors.

Author Summary

Plasmodium falciparum is the main cause of the devastat-ing human disease malaria. This parasitic organism has acomplex lifecycle spanning a variety of different cell typesin the mosquito vector and human host. To adapt andsurvive in these different environments, the parasiteprecisely regulates the transcription of genes throughoutits lifecycle. However, the mechanisms governing tran-scriptional regulation in P. falciparum are poorly under-stood. To date, a single family of specific transcriptionfactors, the Apicomplexan AP2 (ApiAP2) proteins, has beenidentified. These DNA binding proteins are likely to play amajor role in coordinating the development of thisparasite and are therefore of major interest. Here, wedetermine the DNA binding specificities for the entire P.falciparum ApiAP2 family of DNA binding proteins. Ourresults demonstrate that these proteins bind diverse DNAsequence motifs and co-occur in functionally related setsof genes. By mapping these sequences throughout theparasite genome, we can begin to establish a regulatorynetwork underlying parasite development. This studyrepresents the first characterization of a family of DNAbinding proteins in P. falciparum and provides animportant step towards understanding gene regulationin this parasite.

ApiAP2 Binding Specificities in P. falciparum


P. falciparum AP2 Domains Can Recognize MultipleDistinct Sequences

Protein-DNA interaction specificities are determined by the

chemical interactions of amino acids and DNA bases [56]. Side

chain flexibility and DNA distortions allow one DNA binding domain

to interact with multiple distinct DNA sequences. For several of the

AP2 domains there were significant differences among the top scoring

8-mer sequences that were bound, suggesting multi-motif recognition.

Using the Seed and Wobble algorithm [57] we identified alternative

motifs associated with 8-mers of high signal intensity that could not be

explained by the primary motif for 14 AP2 domains (representing 13

ApiAP2 proteins) (Figure S3, Dataset S2). Some AP2 domains only

had a single secondary motif, whereas others had up to four. The

secondary motifs can be described based on their relationship with

the corresponding primary motifs and fall into the broad categories of

end modifications, core changes, variable spacer distances or

alternate recognition interfaces [57] (see Supplemental Text S1).

The ability of an individual domain to bind anywhere from one to

five different DNA sequences would significantly increase the number

of target genes that could be regulated by one factor.

We selected two ApiAP2 proteins for confirmation of secondary

motif binding by electrophoretic mobility shift assays (EMSAs).

Domain 2 of PFD0985w has three predicted secondary motifs in

addition to the primary motif. A plot of the E-scores for all

ungapped 8-mers reveals that the top 100 matches to both the

primary motif and one of the secondary motifs (Figure 2A) are

relatively equal in E-score. Therefore, PFD0985w_D2 should bind

equally well to these two motifs. To test this hypothesis we generated

60 bp oligonucleotides with the specific motif sequence in the center

flanked by random sequences. EMSAs with purified PFD0985w_

D2 demonstrate that both oligonucleotides are bound equally well,

and that the primary motif is capable of out-competing the

secondary motif and vice versa (Figure 2B). No binding is observed

with an unrelated non-specific oligonucleotide, indicating specificity

for the predicted motifs (data not shown). The second ApiAP2 factor

that we selected for confirmation of secondary motifs was

PFL1900w_DLD. The highest scoring 8-mers for this tandem

domain were represented by completely distinct sequences and a

plot of all 8-mers and their E-scores revealed preferential binding

with a primary, secondary, and tertiary motif (Figure 2C).

PFL1900w_DLD was able to shift all three motifs, but with varying

affinities (data not shown for the primary and tertiary motifs), and

competition between the secondary and tertiary motifs revealed a

clear preference for the secondary motif over the tertiary motif

(Figure 2D). These results suggest that the secondary motifs detected

represent bona fide sequences bound by the AP2 domains and the E-

score distributions accurately reflect binding affinities.

Identification of Putative Trans-Factors for PreviouslyPredicted Plasmodium Regulatory Motifs

Both computational predictions and experimental data have

identified a number of DNA sequence motifs upstream of genes

in Plasmodium [17–22,27–32], but the specific trans-factors that

bind to these motifs have mostly remained elusive. For three

cases, we now establish plausible links between the newly

identified AP2 DNA sequence motifs and these previous reports.

Militello et al. identified a specific motif, (A/G)NGGGG(C/A)

(called the G-box), upstream of 8 out of 18 Plasmodium heat shock

genes [22]. The occurrence of this GC-rich motif in the genome

is low (Table S2), suggesting that its presence in upstream

sequences may be significant for transcriptional regulation. The

sequence motif that we have identified for PF13_0235_D1 is

nearly identical to the G-box element (Figure 3A). Furthermore,

the expression profiles of pf13_0235, hsp86 (pf07_0029), and hsp70

(pf08_0054), two heat shock genes containing one or more G-

boxes exhibit a strong positive correlation (r = 0.93) during the

asexual blood stage [2] (Figure 3A), suggesting that PF13_0235

may play a role in regulating hsp gene expression. We performed

EMSAs using both G-box elements of the hsp86 upstream region

and found that PF13_0235_D1 interacts specifically with the G-

box and deletion of both G-boxes is required to completely

eliminate binding (Figure 3B, C). In the presence of only one G-

box, binding is severely reduced (Figure 3B, C) suggesting that

PF13_0235_D1 preferentially interacts with both G-boxes,

perhaps through dimerization (see below). No binding is observed

with an unrelated non-specific oligonucleotide at similar protein

concentration (data not shown). This result is in agreement with

in vivo data from transient transfections, where elimination of G-

box 1 substantially reduced luciferase expression, but did not

completely abolish it [22]. We also tested the G-box from the 59

flanking region of hsp70 for in vitro binding by EMSA, and

confirmed that PF13_0235_D1 binds this sequence in vitro. It is

interesting to note that the binding of this single G-box motif is

similar to that seen for hsp86 after deletion of one G-box,

suggesting that higher affinity interactions require two occur-

rences of this motif.

Likewise, the sequence element bound by PF10_0075_D3,

GTGCA, is enriched in the upstream sequences of genes involved

in merozoite development and invasion [31,58]. Using EMSAs

we find that PF10_0075_D3 binds to the GTGCA motif

upstream of msp1 (pfi1475w), msp10 (pff0995c) and rhopH 3

(pfi0265c) (Figure S4A), and no binding is observed with an

unrelated non-specific oligonucleotide, indicating specificity for

the predicted motifs (data not shown). Previous expression

studies using a rhoptry gene promoter to drive luciferase expres-

sion have demonstrated that the GTGCA motif is important for

rhoptry gene-like stage-specific expression [31]. Combined with

our EMSA results, this suggests that PF10_0075 may play a role

in regulating the expression of invasion-related genes in P.

falciparum.

Finally, a specific 5 bp motif in the 59-upstream region of gbp130

(pf10_0159), GTATT, was previously found to be bound by

unknown nuclear factors in a sequence-specific manner [18]. The

reverse complement of this 5 bp element is nearly identical to the

motif we have identified for PF11_0091. EMSAs using the

Figure 1. PBM derived motifs for P. falciparum ApiAP2 domains. The first column lists the PlasmoDB gene ID and the corresponding AP2domain tested on the PBM. D1, D2, and D3 refer to the AP2 domains numbered from the N- to C-terminus of each protein; and DLD indicates twodomains and a short linker region. Gray shading in this column identifies different AP2 domains from the same protein. Column 2 depicts the relativemRNA abundance profiles for the ApiAP2 genes during the intraerythrocytic developmental cycle (IDC) [2]. Genes that are not expressed during theIDC are in gray. The third column illustrates the number of domains, their architecture and approximate location in the sequence of each ApiAP2protein (protein sizes are not to scale). The protein colours correspond to the number and arrangement of AP2 domains. Proteins with a single AP2domain are in gray, two non-tandem AP2 domains are shaded blue, proteins with two tandem AP2 domains are shown in green, triple non-tandemdomains are in purple, and the tandem double with an additional third domain is in red. The AP2 domain(s) that binds to the corresponding motif isdepicted in yellow. The last column represents the highest scoring motif as a graphical representation of each position weight matrix and visualizedusing enoLOGOS [92]. Motifs previously identified in the literature are marked as follows: * [48]; { [49]; " [50]; and 1 [51].doi:10.1371/journal.ppat.1001165.g001



promoter region of gbp130 and the purified AP2 domain from

PF11_0091 confirm its ability to interact with this sequence

(Figure S4B), while no binding was observed with an unrelated

non-specific oligonucleotide (data not shown), suggesting it is a

possible regulator of GBP130 function. The PBM-derived motifs

are useful to suggest putative targets for the ApiAP2 trans-factors,

especially where previous characterization is available. However,

in vivo assays will be required in all cases to validate these

interactions on a protein-by-protein basis.

Prediction of ApiAP2 Target GenesTo begin to characterize the functional role of ApiAP2 proteins,

we searched the P. falciparum genome for sequences in promoters

and untranslated regions that may serve as regulatory sites for

ApiAP2 binding. As a first analysis, we used our AP2-specific

position weight matrices generated from the PBM data to search

the 59 upstream sequence elements of Plasmodium genes using

ScanACE [59], which lists all matches to our position weight

matrices within the user defined threshold. Although putative

Figure 2. Secondary motifs represent both high- and low- affinity binding sites of ApiAP2 proteins. A) A histogram for PFD0985w_D2enrichment scores (E-scores) of all ungapped 8-mers (gray) demonstrates that both primary (purple bars) and secondary motifs (blue bars) areenriched in the tail area indicating high affinity interactions. A close-up view (inset) indicates that the top 100 8-mer matches for both motifs show amixed distribution of E-scores, suggesting that PFD0985w_D2 will bind both motifs equally. B) EMSA competitions between PFD0985w_D2 primaryand secondary motifs. The arrow denotes shifted probes. Competition with unlabeled probes of either the primary or secondary motif illustrate thatboth compete for binding equally well. No binding is observed in the absence of either motif (data not shown). The same experiment using labeledsecondary motif probe yielded similar results (data not shown). Probes were labeled with biotin and all competitors are unlabeled. C) A histogram forPFL1900w_DLD E-scores of all ungapped 8-mers portrays similar enrichment of motifs at the high end of E-scores. A close-up view of the top 100 8-mers (inset) reveals that there is a clear preference for the primary motif (purple bars) over the secondary (blue bars), and the secondary motif overthe tertiary (orange bars) suggesting different binding affinities. D) EMSA competitions of the PFL1900w_DLD secondary motif with unlabeled probesof the secondary and tertiary motifs, illustrate that the tertiary motif does not compete for binding with the secondary motif. No binding is observedwith an unrelated oligonucleotide probe (data not shown). Shifted probes are indicated by the arrow.doi:10.1371/journal.ppat.1001165.g002



transcription start sites have been predicted [60], actual transcrip-

tion start sites are still poorly defined in P. falciparum [61].

Therefore, we searched 2 kb upstream of the ATG start codon or

until an upstream open reading frame was encountered. While this

search provides a list of all possible motif occurrences determined

from matches to a specific position weight matrix (Datasets S3 and

S4), it is undoubtedly an overestimation of putative target genes. In

reality, the presence of a regulatory element upstream of a gene

does not confirm a regulatory interaction exists, and many motif

occurrences may be inactive [62]. Furthermore, for a regulatory

element to be functional, it needs to be accessible for binding,

which is in part determined by nucleosome occupancy. Nucleo-

some occupancy has been mapped during the intraerythrocytic

developmental cycle (IDC) of P. falciparum [63] and using this data

we were able to determine that between 65 and 97% of our

ScanACE predicted binding sites are accessible (nucleosome-free)

at some point during the IDC (Table S2). This suggests that the

majority of our predictions have the potential to be active;

however, in vivo binding affinities may differ from in vitro

determined affinities, possibly altering the weighting of specific

nucleotide positions within the motifs. Ultimately, the actual target

sequences of each ApiAP2 protein will need to be individually

determined through experimental validation in vivo during the

specific lifecycle stage of interest.

As a test of the ability of our ApiAP2 proteins to bind to the

ScanACE predicted targets we selected a putative target for the

newly annotated ApiAP2 protein PF13_0267; pfc0975c has a

match to the CTAGAA motif at 1469 bp upstream of the start

codon. EMSAs showed that the putative target sequence was

bound by the purified AP2 domain from PF13_0267, while a

mutant oligonucleotide lacking the predicted target sequence did

not exhibit significant binding (Figure S5). Although these results

demonstrate that our ScanACE-predicted target genes provide a

good starting point to search for candidate genes for in vivo testing,

this does not indicate if pfc0975c is a true target of PF13_0267.

Indeed the motif bound by PF13_0267 is found upstream of

almost all genes and in vivo validation will be required to identify

actual targets. Complete AP2 motif occurrence data for the P.

falciparum genome are available to the malaria community at

PlasmoDB (www.plasmodb.org) [64].

Target Gene Refinement Using the IDC TranscriptomeWhile the ScanACE analysis provides a list of all occurrences for

each motif, it is unlikely that the ApiAP2 proteins are binding to all

possible motif occurrences, and instead that they bind to a smaller

subset of promoters. Proteins that are co-localized in the cell or

form sub-cellular structures such as the ribosome have been found

to be transcriptionally co-regulated in other organisms such as

yeast, and often are regulated by the same cis-elements [65]. Genes

that are functionally distinct, but are co-expressed can also be

regulated by the same cis-elements in their upstream regions. To

narrow the ScanACE list to a more informative subset of putative

target genes we used relative mRNA abundance profiles to define

relationships between co-expressed Plasmodium genes [2]. We used

linear regression to determine at each time point the extent to

which each AP2 motif contributes to (or recapitulates) the overall

expression of the genes that contain a given motif in the upstream

regions (see Methods and Supplemental Text S1 for details [66]).

Thus each motif at each time point is associated with a score (i.e.

the fitted regression coefficient), which is positive if genes that have

the motif tend to go up at that time point, or negative if they tend

to go down. These scores define the predicted motif activity at

Figure 3. PF13_0235_D1 binds the G-box and is a putative regulator of heat shock genes. A) Transcript abundance profiles of pf13_0235,hsp86 and hsp70 genes portrays similar timing [2]. B) Partial sequences of EMSA probes from the upstream sequences of hsp86 and hsp70. G-boxmotifs are underlined and shown in red. Mutations in the G-box sequence are underlined in black. C) EMSAs with probes from the upstreamsequence of hsp86 and hsp70 illustrate the ability of PF13_0235_D1 to bind the target sequences. Binding to the hsp86 probe is mediated throughboth G-boxes as mutation of the first or second sequence significantly reduces binding. No binding is observed with an unrelated oligonucleotide(data not shown). The arrow denotes shifted probes. Probes were labeled with biotin and all competitors are unlabeled.doi:10.1371/journal.ppat.1001165.g003



each time point, and an activity profile across the entire IDC.

Activity profiles reflect the predictive effect of individual AP2

motifs on gene expression of a set of target genes at a given IDC

timepoint (Figure 4A), and are therefore independent of the

mRNA expression profiles of the AP2 genes themselves. The

activity profile for each motif was then used to iteratively identify

genes containing the target motif in their 59 upstream regions that

share an expression profile similar to the activity profile. This

provided a refined list of putative target genes that are co-

expressed with one another (Dataset S5).

To illustrate how this approach improved our target predictions

we focus on the G-box motif. The ScanACE predicted target list

for this motif includes 522 genes (Dataset S3), and using the

activity profile-based approach we refine this list to a set of 124

putative co-expressed target genes (Table 1, Dataset S5). A

comparison of the average expression profiles for these genes with

the expression of pf13_0235, the gene for the ApiAP2 factor that

binds the G-box, shows a strong positive correlation (0.97;

Figure 4). Similar comparisons were made for all ApiAP2 factors

and their putative targets (Figure S6), and we observe either

significant positive (r-values from 0.97 to 0.43) or negative

correlations (r-values from 20.94 to 20.56) for many ApiAP2

factors, implying that this protein family may act as both activators

and repressors of target gene expression.

Functional annotation of the predicted targets using the DAVID

bioinformatics resource [67] identified enrichment of genes

involved in specific cellular processes (Table 1). Targets of

PF13_0235_D1, the ApiAP2 factor that binds the G-box motif,

include genes involved in ribosome function or translation and

heat shock response genes. Genes involved in these functions have

previously been suggested to be regulated via the G-box element

[22,33], supporting our target gene predictions. Other notable

examples include the enrichment of targets involved in cell

invasion and host cell entry for the PF10_0075_D3 motif

(GTGCAC) and DNA binding for the MAL8P1.153 motif

(ACACA). The involvement of the GTGCAC motif in invasion

related processes has been independently predicted by three

bioinformatic studies [31–33], while the ACACA motif was

previously associated with DNA replication [31]. Since the

majority of these motifs have not been previously described in P.

falciparum, our prediction of target gene functions are novel and

warrant further characterization.

Similarly, we used a recently published P. falciparum growth

perturbation dataset [68] as an alternative data source to create

activity profiles to refine our target gene predictions (Figure S7,

Dataset S6, Supplemental Text S1). Genes that respond in a

similar manner to a perturbation are more likely to be regulated by

the same factor and we observed narrower target gene lists for

each motif, many of which overlap with the predictions made

using the IDC co-expression data, and others that are novel target

gene predictions (Table 1, Figure 4, Figure S8). Further details on

the perturbation refinement of target genes can be found in the

Supplemental Text S1. Combined, refinement of putative targets

using the high resolution temporal gene expression data [2] and

the perturbation dataset [68] produce manageable gene sets for

further analysis.

Figure 4. Activity profiles for AP2 motifs and refinement of target gene predictions during the IDC. A) The heat map shows the motifactivity profiles based on mutual information content between the motifs and genes expressed at each timepoint of the IDC. Target genes withexpression profiles similar to the activity profiles and containing the motif of interest were identified. B) A plot of the average mRNA abundance fortarget genes with matches to the G-box motif in their upstream sequences is depicted. This is compared with the relative mRNA abundance data forpf13_0235, the ApiAP2 factor that binds to the G-box. There is a strong positive correlation (0.97) between pf13_0235 expression and the expressionof its predicted targets. C) The Venn diagram shows the overlap between IDC co-expressed targets and perturbation co-expressed targets. Half ofPF13_0235 targets are shared between both datasets, and include ribosomal and heat shock genes.doi:10.1371/journal.ppat.1001165.g004



Identification of Motifs Enriched Upstream of var GenesWe also looked at motif enrichment in the upstream regions of

var genes. There are approximately 60 var genes in P. falciparum

that encode the antigenically variant erythrocyte membrane

protein 1 (PfEMP1), which is involved in sequestration of infected

red blood cells in the vasculature [69]. The var genes have been

divided into groups based on their location along the chromosome

(internal or at chromosome ends), the direction of transcription,

and the sequences of their intron and 59 and 39 untranslated

regions [70]. Using our ScanACE prediction of binding sites, we

observed a striking pattern of ApiAP2 motifs that were clustered in

discrete positions of all three types of var promoters (Figure 5). In

the upsB promoters we observed repeated motifs for PFF0200c

that correspond to the previously identified bipartite SPE2 element

[25], located at 22000 to 23000 bp upstream of the ATG start

codon. While PF10_0075_D3 binds to a similar sequence as the

SPE2 element, recent work has demonstrated that PFF0200c is the

primary ApiAP2 factor that binds to this element in vivo [50]. We

also predict the SPE1 element of upsB var genes at 21200 bp [25],

which matches to the motif we have identified for PF14_0633. In

addition to these previously identified sequence elements, we

predict binding sites for PF11_0442, which binds to the sequence

GCTAGC (Figure 5). Matches to this motif are conserved in all

three major types (A, B and C) of var genes. The presence of

Table 1. Number of target genes predicted using the IDC and perturbation refinements, along with the major functionalannotations of target genes associated with each motif.

AP2 domain*

Number of targetsfrom IDC orperturbationrefinements

Functional annotationof targets [67]

Total numberof genes inannotation term

Number ofpredicted targetsin annotationterm P-value

BonferronicorrectedP-value

PF07_0126_DLD 802802

proteasome complexapicoplast

31493

22107

1.3610211

6.0610274.861029

2.261024

PF14_0633 221 protein amino acid phosphorylation 130 14 6.261026 0.006

PF13_0267 226226

ribosome biogenesis and assemblypurine metabolism

3596

1115

1.361028

3.5610281.361025

2.961026

PF14_0079 430249

zinc ion bindingentry into host

1996

264

9.761025

4.8610240.080.4

PF11_0404_D1 309531

protein serine/threonine kinase activityzinc ion binding

106199

1631

2.661025

3.3610250.020.03

PF13_0097 10341034

translationRNA metabolic process

281275

11592

1.5610222

2.56102111.5610219

2.661028

PF13_0235_D1 12488

ribosomal subunitresponse to unfolded protein

9534

144

8.261028

0.023.061025

1

PF10_0075_D1 24 nucleic acid binding 580 7 0.001 0.7

PF10_0075_D2 949949

DNA replicationproteasome complex

6131

3720

1.7610215

1.2610281.8610212

4.361026

PF10_0075_D3 283283

entry into host cellnucleosome

612

56

3.261025

3.5610250.030.01

PFL1075w 10581058

gene expressionRNA metabolic process

516275

210116

2.3610250

3.96102262.3610247

3.9610223

PFL1900w_DLD 617617

RNA metabolic processRNA processing

275119

6133

8.6610214

5.76102108.7610211

5.761027

PFE0840c_D2 9898

generation of precursor metabolites and energymitochondrion

118117

1312

2.561027

1.7610252.561024

0.006

PF14_0533 676386

DNA replicationpost-translational protein modification

61216

2530

3.461029

3.5610273.461026

3.561024

PFF0670w_D1 772772

gene expressiontranslation

516281

177107

1.1610240

7.96102271.1610238

7.9610224

PFF0670w_D2 576576

gene expressioncytosolic ribosome

51646

13433

4.5610229

4.26102234.6610226

1.5610220

PFF0200c_DLD 114 gene expression 516 28 1.161025 0.01

MAL8P1.153 986986

DNA replicationapicoplast

61493

33117

1.9610211

6.2610279.661029

2.361024

PF11_0091 359359

proteasomevesicle mediated transport

3150

1713

8.0610212

8.7610252.961029

0.08

PF11_0442 223 DNA metabolic process 152 19 1.161025 0.01

PFD0985w_D1 710935

DNA replicationapicoplast

61493

38132

5.6610222

1.56102125.6610219

5.4610210

PFD0985w_D2 10241024

gene expressiontranslation

516281

212119

8.0610250

3.96102268.0610247

4.0610223

*AP2 domains are listed in order of IDC expression as in Figure 1.doi:10.1371/journal.ppat.1001165.t001



multiple ApiAP2 binding sites upstream of var genes suggests

multiple ApiAP2 factors may be recruited for binding upstream of

the var genes. var promoters are silenced by default [71], and it is

possible that this silencing is maintained by the co-ordinated action

of multiple ApiAP2 factors. Further investigation of these discrete

motif-enriched sites will be required to determine the precise role

of additional ApiAP2 proteins in var gene regulation.

Target Gene Prediction in P. vivaxThe IDC transcriptome of P. vivax [72] suggests that the

regulation of development follows a similar cascade of gene

expression as that seen for P. falciparum [2,6]. All P. falciparum

ApiAP2 proteins have syntenic homologues in P. vivax and are

expressed at a similar stage of development during the IDC with

the exception of pf14_0471 (pv118015) which is shifted from

trophozoite to late schizont stage [72] (Figure S9A). AP2 domains

are highly conserved across all Plasmodium spp. and will likely bind

the same motifs. It follows that the ApiAP2 proteins may regulate

similar or related target genes in P. vivax compared to P. falciparum.

We calculated activity profiles using the P. vivax asexual blood

stage transcriptome data [72] (Figure S9B) and as seen for P.

falciparum, most of the motifs are associated with activation or

repression of target genes at one or more timepoints. However, a

comparison of the target gene lists for each motif in P. falciparum

and P. vivax shows that the conservation of putative targets is low,

ranging from 0 to 53% (Table S3). This implies that although the

AP2 DNA binding domains are highly conserved, some of the

regulons across these species have diverged and regulation of

orthologous genes has evolved independently. It should be noted

that a comparison of target genes in non-blood stages, including

the mosquito stage, demonstrates substantial statistically significant

conservation of motifs among co-regulated genes in P. vivax and P.

falciparum [73]. Therefore it will be important to identify the actual

target genes bound in vivo for each motif to determine the actual

extent of conservation between species.

Target Genes in Non-Blood Stages of DevelopmentWhile the above analyses are limited to transcriptional

regulation during the blood stage of the lifecycle, ApiAP2 function

is not limited to the IDC. Accordingly, we analyzed gene

expression data from P. falciparum gametocytes, zygotes and

sporozoites [6,10]. Activity profiles for ApiAP2 motifs in

gametocyte data revealed activity for a number of the PBM

derived motifs during gametocytogenesis (Figure S10A). We found

two motifs to be active in zygotes, including the previously

identified zygote motif for the P. berghei orthologue of PF11_0442

(PBANKA_090590), as well as the CACACA motif, which is

bound by PF13_0026 (Figure S10A, Dataset S7). Activity profiles

for AP2 DNA motifs in sporozoites identify PF14_0633,

PFD0985w_D2, and PFF0670w_D1 as potentially active AP2

domains during this stage (Figure S10A). Since there is currently

no liver stage data available for Plasmodium species that infect

humans, we used data from the rodent malaria species P. yoelii [9].

Activity profiles for our PBM derived motifs in the P. yoelii liver

stage yielded a number of motifs that are potentially active during

this stage (Figure S11). Further discussion of the non-blood stage

active motifs can be found in the Supplemental Text S1.

Discussion

Understanding the molecular mechanisms and the regulatory

processes that underlie gene expression during the development of

P. falciparum is a major challenge in malaria research. The ability to

map the recognition sites of DNA binding proteins genome-wide

enables an improved understanding of how trans-factors regulate

gene expression and has been undertaken for only a few large

eukaryotic families of transcription factors [54,57,74–76]. Here,

we have comprehensively characterized the P. falciparum ApiAP2

protein family and established their preferred DNA recognition

motifs. A number of findings strongly implicate these factors as

major regulators of gene expression in P. falciparum. First, the

expression of the ApiAP2 genes at distinct times throughout the

IDC suggests they are available to regulate target genes

throughout the entire 48-hour blood stage of the parasite. Second,

the diversity of sequences bound by these domains is sufficient to

account for the full cascade of gene expression observed in the

IDC. Furthermore, ApiAP2 genes form an interaction network

with themselves during the IDC (Figure S12), suggesting that in

addition to regulating target genes they may also regulate their

own expression. For all three instances where in vivo data on

binding sites for ApiAP2 proteins are available [49–51], our PBM

Figure 5. ApiAP2 motifs are conserved in var gene promoters.Matches to ApiAP2 motifs were identified using position weightmatrices for each motif. Searches were performed on 3 kb upstream ofthe ATG start codon or until the next upstream gene was encountered(shorter lines). The presence and position of motifs are conserved in thepromoters of different types of var genes. The previously describedSPE1 and SPE2 motifs in upsB var genes were found as well asoccurrences of the PF11_0442 motif in all types of var genes.doi:10.1371/journal.ppat.1001165.g005



derived motifs are excellent matches, emphasizing the quality of

these data and the robustness of the PBMs at identifying preferred

sequence elements. Finally, half of the motifs that we identified are

nearly identical to motifs that were independently predicted

computationally as putative cis-elements in the P. falciparum

genome [27–29,31–33].

Our success rate for identifying DNA binding specificities (20

out of 27 ApiAP2 proteins, 74%) using the PBMs is comparable to

results obtained using the same technology with other transcrip-

tion factor families from yeast and mouse (40–85% successful)

[54,57,76]. For those AP2 domains that did not yield a result,

there are numerous technical reasons why we may fail to detect

binding. Although we were able to successfully express all of our

GST-fusion constructs, possible reasons for failure to detect

binding events include insufficient protein concentration, low

protein stability, binding conditions (e.g. ionic strength) used, or

low-affinity binding (undetectable by PBM). Another possibility is

simply that some predicted AP2 domains lack specific DNA

binding activity altogether. As mentioned above, the ApiAP2

proteins vary dramatically in size, including four proteins that are

less than 40 kDa (Figure S1). Only one of the four smallest ApiAP2

proteins (,300 amino acids) binds to DNA (PF13_0026). Despite

our testing both full-length ApiAP2 proteins and isolated AP2

domains from these small proteins, we could detect no DNA

binding by PBM. This is surprising given their lack of any other

predicted functional domains.

Both computational prediction of motifs [22,31–33] and

experimental data [25,49–51] have identified a number of

regulatory elements involving repeated iterations of the same

motif. One established way to recruit multiple copies of the same

factor to a particular site in the genome is through the formation of

dimers or multimers of the same protein. A crystal structure has

recently been solved of the AP2 domain from PF14_0633, which

reveals that the AP2 domain forms a dimer when bound to DNA

[77]. This structure suggests that other ApiAP2 proteins may also

form homo- or heterodimers [78], thereby recognizing multiple

DNA sequence motifs in concert. Further support for this idea is

seen in our EMSA analysis of PF13_0235_D1, which shows that

higher affinity binding to the G-boxes upstream of hsp86 (Figure 3)

occurs when multiple copies of the motif are present. Similar

results were obtained for PF10_0075_D3 and the predicted

rhopH 3 target (Figure S4A) suggesting that AP2 domain

dimerization may enhance binding to these sequences. Our

ScanACE predictions of target genes identify motif repeats in

upstream regions (Dataset S3), which may allow for tighter control

of target gene expression by the ApiAP2 factors. Similarly,

heterodimer formation may facilitate combinatorial regulation of

gene expression at co- motifs. Evidence for such interactions can

be found in yeast two-hybrid assays that have detected associations

between ApiAP2 proteins [79]. Taken together, our genome-wide

motif predictions and the ability of plasmodial AP2 domains to

form dimers implies that these factors likely work together to

regulate target gene expression.

The extremely high level of conservation (.95% identity) for

each AP2 domain across all Plasmodium spp. [43] suggests that

orthologues from other species will bind to similar DNA sequence

motifs. Indeed, motifs for the P. falciparum AP2 domains of

PF14_0633 and PF11_0442 are matches to the experimentally

determined motifs for their P. berghei orthologues (AP2-Sp and

AP2-O, respectively) [49,51]. However, while the cis-elements

bound by individual AP2 domains may be conserved across

species, our predicted IDC target gene sets for ApiAP2 proteins

appear to differ extensively. This is common in other eukaryotic

organisms, where DNA binding domains are highly conserved

across species, but downstream target genes are divergent [80–85].

Our data suggests that this may be true for Plasmodium spp., as

demonstrated by the divergence of IDC target gene sets in P. vivax

and P. yoelii compared to P. falciparum, which contrasts with the

almost perfect conservation of AP2 domains and the similar

temporal expression of ApiAP2 genes. We previously showed that

the orthologous AP2 domains from PF14_0633 in P. falciparum and

its distant Apicomplexan relative C. parvum (cgd2_3490) bind

virtually identical sequence elements [48], but their predicted

regulons had virtually no overlap. However, there are some

examples of transcription factor binding site conservation among

specific groups of target genes. For example, the G-box element

has been predicted to regulate heat shock genes in both C. parvum

[86] and P. falciparum [22], and both the PF14_0633 (TGCA-

TGCA) and PF10_0075_D3/PFF0200c_DLD (GTGCAC) motifs

are conserved among sporozoite and merozoite invasion genes in

P. falciparum, P. vivax, P. yoelii, and P. knowlesi [87]. A better

assessment of target gene conservation between species will be

possible with more accurate target gene lists from chromatin

immunoprecipitation experiments for each individual ApiAP2

factor. Indeed, this has recently been demonstrated in the asexual

blood stages for PFF0200c [50], and only a subset of predicted

targets were actually bound in vivo by this factor. This is also

likely to be true for other ApiAP2 factors and further work

identifying functional binding sites will clarify the level of con-

servation of transcription factor binding sites among the different

Plasmodium spp.

Combinatorial gene regulation is an important aspect of

transcription in many organisms. It controls the level of gene

expression, the precise timing of expression, and determines the

ability of a regulatory circuit to respond differently to a wide

variety of extracellular signals. The finding that there are a

relatively small number of specific transcription factors in P.

falciparum prompted the hypothesis that combinatorial gene

regulation plays an important role in the parasite [29]. Our

finding that some ApiAP2 proteins can bind more than one

sequence element significantly increases the potential complexity

of the regulatory network. We identified secondary DNA binding

preferences for 14 AP2 domains. These secondary motifs allow

one AP2 domain to regulate a much broader range of targets than

initially predicted from our ScanACE analysis using only the

primary motifs. Precedent for this has been seen in yeast where the

transcriptional activator, HAP1, binds two completely different

regulatory sequences, allowing for the regulation of target genes

with different promoter elements [88]. A similar observation was

made in a recent PBM analysis of 104 mouse transcription factors,

where it was found that almost half of the TFs recognized multiple

sequence motifs [57]. A re-analysis of previously generated

chromatin immunoprecipitation – microarray (ChIP-chip) data

illustrated that these newly identified alternate motifs were also

bound in vivo [57]. Similar in vivo data will be required to fully

elucidate the role of individual ApiAP2 motif occurrences on

target gene functions; however it is evident from our data that the

ApiAP2 factors have sufficient diversity in sequence recognition to

potentially regulate all P. falciparum genes.

While it is clear that the ApiAP2 factors bind DNA and recent

work has begun to explore their contribution to transcriptional

regulation [49,51], these factors are also capable of binding DNA

as scaffolding and recruitment proteins [50]. This finding opens up

new possible functions for this family of DNA binding proteins.

The next step in understanding ApiAP2 function will be to address

the role of other domains in these proteins. The majority of

ApiAP2 proteins are predicted to encode extremely large proteins,

yet nothing is known regarding other functional domains outside



of the AP2 domain. Yeast two-hybrid assays have identified

interactions between ApiAP2 proteins and chromatin modifying

proteins [79], which could help recruit ApiAP2 proteins to target

sites in the genome. How and when ApiAP2 proteins are targeted

to the nucleus and if this is actively regulated also remains

unanswered. Our global mapping of ApiAP2 motif preferences

represents the first characterization of a Plasmodium family of DNA

binding proteins and provides a starting point to investigate

transcriptional control in P. falciparum. These results provide an

important step toward understanding the role of these proteins as

major regulators throughout all stages of parasite development in

Plasmodium spp. and other related Apicomplexan species.

Materials and Methods

Cloning, Expression, and Purification of P. falciparumApiAP2 Domains

Domain boundaries were defined as in [43] and extensions were

made based on sequence homology both 59 and 39 of the AP2

domains amongst Plasmodium spp. orthologues, as well as using

structural predictions from the online secondary structure

prediction server Jpred3 [89]. In total 77 different versions of

ApiAP2 domains from P. falciparum as well as one from P. berghei

were cloned into pGEX-4T1 (GE Life Sciences) to create N-

terminal glutathione S-transferase (GST) fusions (Figure S2).

Proteins were expressed in BL21-CodonPlus(DE3)-RIL cells

(Stratagene) with 0.2 mM IPTG at room temperature and affinity

purified using glutathione resin (Clontech). The purity of each

protein was estimated by silver stained SDS-PAGE and yields

were calculated based on absorbance at 260 nm and specific

molar extinction coefficients. All protein concentrations include

contaminating products and will be an overestimation of the actual

AP2 domain amounts.

Protein-Binding Microarrays (PBMs)All constructs in Figure S2 were tested at least once on the

PBMs, and positive motifs were confirmed at least twice on

independent arrays. The PBM experiments were performed as

previously described [53]. Briefly, custom designed oligonucleotide

arrays are double-stranded using a universal primer, incubated

with GST-AP2 fusion proteins, visualized with Alexa-488

conjugated anti-GST antibody, and scanned using an Axon

4200A scanner. Proteins were used at the maximum concentration

obtained from purification and represent one-fifth of the total

reaction volume used on the PBM. In this study three different

universal platforms were used covering all contiguous 8-mers as

well as gapped 8-mers spanning up to 10 positions. After data

normalization and calculation of enrichment scores [53,55] the

‘‘Seed-and-Wobble’’ algorithm was applied to combine the data

from two separate experiments and create position weight matrices

(PWMs) [55]. An enrichment score cut-off of 0.45 was used to

distinguish high affinity binding data from low affinity and non-

specific binding. The score for each 8-mer reflects the affinity of a

DNA binding domain for that sequence, with higher scores

representing tighter interactions [55]. Secondary motifs were

identified by running the ‘‘rerank’’ program until E-scores below

0.45 were obtained [55]. The PBM analysis suite was downloaded

from the Bulyk lab (http://the_brain.bwh.harvard.edu/PBMAna-

lysisSuite/index.html). For public access, all motifs have been

deposited in the UniPROBE database [90].

Electrophoretic Mobility Shift Assays (EMSAs)N-terminal GST fusions of the ApiAP2 domains were puri-

fied as described above. Single-stranded HPLC purified 59

biotinylated oligonucleotides were purchased from Integrated

DNA Technologies (http://www.idtdna.com) and annealed

with complementary oligonucleotides to create double-stranded

probes (Table S4). EMSAs were performed using the LightShift

Chemiluminescent EMSA kit (Pierce). Briefly, purified protein

was incubated with 50 ng/mL of poly(dI-dC) and 10 fmol of

biotinylated probes. Competitor DNA was added in 50 or 250

fold molar excess. All reactions were incubated in the kit EMSA

buffer with 2.5% glycerol, 5 mM MgCl2, 10 mM EDTA, 50 mM

KCl, and 0.05% NP-40 at room temperature for 20 minutes.

Electrophoresis and transfer to Nylon membrane (Hybond) was

performed according to the manufacturer’s instructions. The

Chemiluminescent Nucleic Acid Detection Module (Pierce) was

used according to the manufacturer’s instructions to visualize the

probes.

Identification of Potential Target Genes Using PBMDerived Position PWMs

2 kb-long upstream regions (or up to the nearest ORF) were first

extracted from whole genome sequences and associated gene

annotation data (PlasmoDB 6.0). PBM motifs were trimmed down

to their 6 most informative consecutive motif positions (motif

cores). Then, we determined all core PBM motif occurrences in

the 2 kb regions using the ScanACE approach [91]. G+C content

was set to 13.1% in P. falciparum, 42.8% in P. vivax and 20.1% in P.

yoelii. Score threshold was set to the average score of randomly

drawn sequences from the PBM PWMs, minus two standard

deviations (this is the default ScanACE setting).

Refinement of Target Gene ListsIn order to identify candidate target genes for each AP2, we

reasoned that these target genes should be co-expressed and should

share the AP2 binding site we identified using PBMs. Thus, we first

identified groups of genes that are co-expressed across multiple

experimental conditions or multiple time points (e.g., in the IDC).

Then for each AP2 motif, we determined in which of the groups the

motif was over-represented. For each of these groups, we extracted

the genes associated with one or more motif occurrences. Thus,

target genes in this definition can come from multiple co-expression

groups (and not all genes in these co-expression groups end up in the

target list because not all genes in these groups will have a motif

occurrence in their promoter). In order to define co-expressed gene

groups, we used the k-means approach together with the Pearson

correlation. Motif scanning was performed using the ScanACE

approach [91] as described above. In order to determine functional

motif score threshold, we used an information-theoretic procedure

analogous to that used in FIRE [27]: briefly, we determined the

motif score threshold such that the resulting motif occurrences best

explain the co-expression clusters obtained by k-means. At a given

motif score threshold, motif over-representation in each cluster was

assessed using the hypergeometric distribution; to correct for

multiple testing (i.e. multiple clusters being evaluated), we used

the Benjamini-Hochberg procedure; corrected p-values corre-

sponding to an estimated overall FDR of 0.25 were considered

significant and the genes associated with motif occurrences in these

clusters were extracted. Because the k-means is dependent on

initialization, we repeated the entire procedure 10 times; genes

extracted 3 times or more (out of 10) were considered as candidate

target genes. Thus, only genes associated with the considered motif

and that are consistently found as co-expressed together with other

genes sharing that same motif end up as candidate target genes in

our analysis. More detailed methods are available in the

Supplemental Text S1.



Accession NumbersPlasmoDB (www.plasmodb.org) accession numbers for genes

and proteins discussed in this publication are: hsp86 (PF07_0029);

hsp70 (PF08_0054); msp1 (PFI1475w); msp10 (PFF0995c); rhopH 3

(PFI0265c); gbp130 (PF10_0159); AP2-O (PBANKA_090590);

AP2-Sp (PBANKA_132980).

Supporting Information

Supplemental Text S1 Supplemental results and discussion.

Found at: doi:10.1371/journal.ppat.1001165.s001 (0.13 MB PDF)

Figure S1 Size distribution of ApiAP2 proteins. Proteins range

in size from 200 amino acids to over 4000, with the four smallest

ApiAP2 proteins having less than 500 amino acids. Bars are colour

coded based on the number of AP2 domains in each protein.

Found at: doi:10.1371/journal.ppat.1001165.s002 (0.38 MB TIF)

Figure S2 ApiAP2 domains tested on PBMs. ApiAP2 proteins

are listed in order of size. Domains were cloned into pGEX-4T1 to

produce N-terminal GST fusions. Proteins were expressed and

purified from E. coli and tested in duplicate on protein binding

microarrays (PBMs). D1 indicates the AP2 domain closest to the

N-terminus; D2 and D3 are the AP2 domains following D1 going

from the N- to C-terminus of the protein; DLD indicates two

domains and a short linker region (Domain - Linker - Domain); ext

at the end of the domain number indicates an extension of the

original cloned domain at either or both of the N- and C-termini.

Enrichment scores above 0.450 were considered significant, and

no result indicates an E-score below this cut-off. PFL1900w_DLD

has a poly-asparagine tract that increases its linker length by 39

amino acids. This expanded linker is absent in the P. berghei

orthologue (PB000218.00.0) of PFL1900w, while the AP2 domain

sequences are 99% identical. To test the effect of the PFL1900w

expanded linker on DNA binding we generated a GST fusion

DLD construct for the shorter P. berghei orthologue. Both

constructs exhibited identical DNA binding specificity.


Figure S3 AP2 domain secondary motifs. Secondary motifs

found for ApiAP2 proteins and their associated enrichment scores.

E-scores greater than 0.450 were considered significant. The final

column lists the relationship of the secondary motif to the primary

motif using the following descriptions: end modification is a

change in nucleotide specificity at either or both the 59 and 39 ends

of the motif, alternate recognition interface is a motif that is

unrelated to the primary motif, variable spacer distance is an

insertion or deletion in the middle of the motif, and core change is

a change in nucleotide specificity in the middle of the motif.


Figure S4 PF10_0075_D3 and PF11_0091 bind Plasmodium

regulatory motifs. A) Partial sequences of the EMSA probes from

the upstream sequences of rhopH3, msp1 and msp10. The

PF10_0075_D3 motif is underlined in red and mutations are

underlined in black. EMSAs using these probes illustrate the

ability of PF10_0075_D3 to specifically bind the target sequences

(shifted complexes are denoted with an arrow). No binding was

observed with an unrelated oligonucleotide. Probes are biotin

labeled and all competitors are unlabeled. B) EMSA using the

gbp130 upstream sequence demonstrates that PF11_0091 binds to

this sequence, but not to a non-specific probe. Sequences are

indicated as in (A).


Figure S5 PF13_0267 binds to a sequence upstream of a

ScanACE predicted target gene. A) Transcript abundance profiles

of pf13_0267 and a predicted target gene, pfc0975c, show similar

timing [7]. B) EMSA using the upstream sequence of pfc0975c, a

putative target of PF13_0267. Biotinylated probe is specifically

shifted with increasing amounts of the purified protein (designated

by the arrow) and this shift is competed with unlabeled probe

DNA. No shift is observed with an unrelated oligonucleotide (data

not shown). Partial probe sequences are shown below the gel, with

the PF13_0267 target motif underlined in red and mutations of the

motif underlined in black.


Figure S6 Correlation of ApiAP2 mRNA abundance and

expression of putative target genes. Average targets represents

the average mRNA abundance profiles during the IDC for all

genes in Dataset S5. mRNA abundance profile data was taken

from [7]. The correlation coefficients are provided in the bottom

right of each plot.


Figure S7 Activity profiles for AP2 motifs using perturbation

data. To refine our list of target genes we defined activity profiles

for each motif using the IDC perturbation data [16]. Activity

profiles are grouped by drug treatments and their corresponding

controls. Each row represents the motif activity profiles and

timepoints are from left to right within each treatment. Specific

details for each perturbation experiment can be found in [16].


Figure S8 Overlap between predicted IDC and perturbation co-

expressed targets. Blue circles represent the predicted IDC co-

expressed targets and the yellow shaded circles are the

perturbation co-expressed targets. The overlap between the two

gene lists is shown in green. The numbers indicate the number of

unique gene IDs in each dataset. The AP2 domain that binds to

the corresponding motif is listed above each Venn diagram.


Figure S9 ApiAP2 IDC expression and activity profiles for the

AP2 motifs in P. vivax samples. A) A comparison of IDC mRNA

abundance profiles for the P. falciparum ApiAP2 proteins [7] with

motif data and their P. vivax orthologs [29]. Expression is similar

between the two species. Gray indicates data not available. B) To

compare target genes for each motif in P. falciparum and P. vivax,

activity profiles were defined using three P. vivax isolates [29]. The

columns in the heat map represent the nine timepoints and rows

are the motif activity profiles. ApiAP2 proteins are ordered as in

Figure 4.


Figure S10 Activity profiles for AP2 motifs in different stages of

the P. falciparum lifecycle and target gene predictions. To identify

motifs that function in different stages we used data from across

the lifecycle [8,10]. Motif activity profiles for the IDC are in

duplicate, using either sorbitol or temperature synchronized

parasites. Data for gametocyte expression is from a 14 day

experiment and zygotes, ookinetes, and sporozoites represent a

single timepoint. Each row is the activity profile for an AP2 motif.


Figure S11 AP2 motif activity profiles during the P. yoelii liver

stage. Motifs for the P. falciparum ApiAP2 proteins were used to

establish activity profiles in the P. yoelii liver stage (LS) [20].

Columns are grouped based on the hour post invasion in the liver

(24, 40, or 50 hours). At each timepoint LS samples were

compared to a range of samples: mosquito oocyst sporozoites

(ooSpz), mosquito salivary gland sporozoites (sgSpz), to alternate

LS timepoints, and to blood stage schizonts (sSchz) and mixed



blood stage samples (BS). ApiAP2 proteins are ordered as in

Figure 4.


Figure S12 P. falciparum IDC ApiAP2 regulatory network.

ApiAP2 genes are targets of other ApiAP2 factors. ApiAP2 genes

are arranged in order of expression during the IDC in a clockwise

manner starting at PF07_0126. Arrows pointing away from an

ApiAP2 gene indicate that it potentially regulates the target factor

by binding to motifs in the target upstream region. ApiAP2 genes

coloured in green are expressed during the IDC, but did not

exhibit DNA binding specificity on the PBMs. Genes in yellow are

expressed during the IDC and bind to specific DNA sequences

and genes in blue also bind DNA, but are not expressed during the

IDC.


Figure S13 ApiAP2 proteins that bind the CACACA motif. A)

Three of the ApiAP2 factors that bind the CACACA motif are

expressed in the late stages of the IDC as shown by mRNA

abundance profiles [7]. B) An alignment (performed using

ClustalW; www.ebi.ac.uk/clustalw) of the AP2 domains for these

three factors demonstrates a high level of similarity (52%) in the

predicted b-sheets (gray arrows above the alignment); which likely

contain the DNA binding residues. Identical residues are

highlighted in red and similar residues in yellow. Secondary

structure predictions were made using Jpred3 [5]. Addition of

PF13_0026 to the alignment, the one CACACA-binding factor

that is not expressed in the IDC, shows that the sequence of this

AP2 domain is more divergent. (C) Phylogenetic tree of the

predicted b-sheet regions of the AP2 domains. The tree

demonstrates that the three IDC expressed ApiAP2 factors that

bind the CACACA motif are more similar to one another than to

any other AP2 domain. The tree was made using PhyML, using

maximum likelihood with a LG protein evolution model.


Table S1 Similarity E-values calculated using the STAMP tool

between ApiAP2 position weight matrices.

Found at: doi:10.1371/journal.ppat.1001165.s015 (0.02 MB XLS)

Table S2 Distribution and accessibility of ApiAP2 binding sites.


Table S3 Conservation of IDC ApiAP2 targets between P.

falciparum and P. vivax.


Table S4 Oligonucleotides used in EMSAs.


Dataset S1 Position weight matrices for all AP2 domains that

bound DNA in PBM experiments.


Dataset S2 Position weight matrices for all secondary AP2

motifs.


Dataset S3 ScanACE results for all AP2 motifs. ScanACE

results for all ApiAP2 motifs. The location, orientation, and

sequence of each motif match in upstream regions are indicated.

Found at: doi:10.1371/journal.ppat.1001165.s021 (8.80 MB ZIP)

Dataset S4 Motif occurrence across the P. falciparum genome.


Dataset S5 IDC co-expressed predicted targets for all motifs.


Dataset S6 Perturbation co-expressed predicted targets for all

motifs.


Dataset S7 Sporozoite and zygote predicted targets of ApiAP2

proteins.


Acknowledgments

We would like to thank the many people who have contributed to this

project including Tuo Li, Louis Sarry, Kate Wiles, Holly Cardoso, Ilsa

Leon, Anne Hempel, Andrew Gehrke, Martha Bulyk, and Alejandro

Ochoa. We thank Moriah Szpara, Marcus Noyes, Alison Hottes and

Heather Painter for critical reading of the manuscript.

Author Contributions

Conceived and designed the experiments: TLC EKDS KLO OE ML.

Performed the experiments: TLC EKDS. Analyzed the data: TLC EKDS

KLO OE ML. Contributed reagents/materials/analysis tools: KLO OE.

Wrote the paper: TLC ML.

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